Many challenges exist in wholesale pricing, particularly in used vehicle wholesale pricing. For example, one challenge is to accurately estimate the wholesale value of a used vehicle given its trim, options, condition, mileage, and other factors that could potentially affect the valuation process. Also, intelligently processing the raw data is also difficult, given a large portion of the vehicle condition terms are in free-text form.
One existing method estimates the wholesale value for used cars at a fixed level of vehicle grouping, independent of vehicle conditions. For example, all 2010 Ford Explorers would be considered to have the same value. This method has several drawbacks. For instance, the identified value may be inaccurate as a result of a scarcity of data, especially for older vehicles. Furthermore, if vehicle conditions are ignored, these fixed estimated values can be extremely inaccurate. For instance, the value of a vehicle that is in excellent condition may be thousands of dollars higher than the value of a vehicle of the identical make, model and year that is in poor condition.
The inability to accurately determine the value of an item such as a used vehicle may make it difficult for an automobile dealer to buy and sell used vehicles. Consider an automobile dealer who must decide how much to offer for a vehicle taken as a trade-in. The amount of money offered by the dealer for the trade-in is affected by the decision to wholesale the vehicle or resell it at retail, the cost of repairing or reconditioning the vehicle, transportation costs, and so on. If the dealer cannot accurately determine the amount to offer for the trade-in, he may lose money on the transaction.
It would therefore be desirable to provide improved means for determining values of items such as used vehicles.